System-of-Systems Engineering - Liophant Simulation

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Modeling and Simulation Challenges in SoS Engineering• Physical experiments are typically infeasible or limited– Computer simulations are required, and are oftencomputationally intensive and time consuming– Verification and Validation is a challenge• SoS are complex– Limits available modeling techniques– Often results in high dimensionality• SoS have a large and diverse alternative space– Unfathomable number of combinations– Need to speed up modeling and simulation– Can be challenging to visualize results• SoS are stochastic in nature– For a given set of inputs, the results are a distribution– Behavior is often modal in natureDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu22
Extension to Systems-of-Systems Analysis• The DoD shift to capabilitybasedacquisition is mergingthe operations research andsystems design communities• The impact of systems andsub-systems is oftennegligible when compared totactics, doctrine, and strategy• Methods for efficientscenario construction,surrogate creation, andoptimization for SoS areneededInfinite FOR FixedTarget SensorGIT Battle ManagerIn-TheaterBasingTarget Latitude373635AirborneSensorLRS PlatformsHigh Speed Missile34Baghdad33323130Denied Basing39 40 41 42 43 44 45 46 47 48Target LongitudeDistribution of Successful Engagementsin Iraq (Desert Storm Scenario)Perfect CommunicationsJDAM-likeLow Speed MissileDefensesThrust/Weight Ratio1.51.41.31.21.110.90.80.70.60.50.40.3TCT Finder/ShooterTCT’sIADSSuccessful Engagements20 30 40 50 60 70 80 90 100 110 120 130 140 150Wing Loading (lb/ft 2 )Successful Engagements Favor HighWing Loading and Low Thrust/WeightRatio (Bomber-like)AreaDominance(Multi-Hit)High ValueTargets(Fixed)TargetBomberDead SAMsBattle ManagerMap Image c/o National Geospatial Intelligence Agency (www.nga.mil)Targets NeutralizedHigh SpeedLess SuccessfulPlatform SpeedBest Speed~ 750 knotsMunition RangeThe Complexity of the Systems-of-Systems Analysis Problem Often Confounds AnalystsDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu23
Page 1 and 2: Developing Methods and Techniques f
Page 3 and 4: The Aerospace Systems Design Labora
Page 5 and 6: Motivation- Emphasis on “Early-Ph
Page 7 and 8: What is a system?“A set of functi
Page 9 and 10: System of Systems• “A set or ar
Page 11 and 12: What is SoSE?• System of Systems
Page 13 and 14: The Evolution of New Ideas“All tr
Page 15 and 16: What is needed for this New Paradig
Page 17 and 18: An Architecture-based Approach to S
Page 19 and 20: The System Alternative Space• The
Page 21: The Architecture-based Technology E
Page 25 and 26: Fundamental Properties of a Complex
Page 27 and 28: Enablers for Complex SoS• Design
Page 29 and 30: Design of Experiments• Design of
Page 31 and 32: Design of Computer Simulation• Co
Page 33 and 34: Agent-Based Behavioral Modeling•
Page 35 and 36: System Dynamics Modeling• System
Page 37 and 38: Discrete Event Simulations• Discr
Page 41 and 42: Surrogate ModelsWhy do we use surro
Page 43 and 44: Challenges to Surrogate Modeling fo
Page 45 and 46: Fitting Modal ResponsesDeveloping M
Page 51 and 52: Pareto Optimal Solutions in Many Di
Page 53 and 54: Interactive Electronic Design Revie
Page 55 and 56: Collaboration and Integration in So
Page 57 and 58: Concluding Remarks• System of Sys
Page 59 and 60: Selecting a DesignDeveloping Method
Page 61 and 62: A New Paradigm Shift: Simulation Ba
Page 63 and 64: Which are simple? Which arecomplica
Page 65 and 66: What is a Markov Chain• Markov Ch
Page 67 and 68: Markov Chains• The transition pro

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